This paper addresses the spoofing detection issue for the Global Positioning System (GPS) based on radio frequency fingerprinting (RFF). We first introduce a new RFF feature in the post-despreading domain of GPS signal processing to better capture the hardware characteristics of GPS satellites. We model the new RFF feature as grayscale constellation images (GCIs) and provide in-depth analysis to show the hardware characteristics that can be captured by GCIs. Using this feature, we develop a deep-learning based spoofing detection framework named GCI-GANomaly, which applies a generative adversarial network (GAN) with a cosine latent anomaly scoring strategy for robust detection. We evaluate the detection accuracy and false positive rate (FPR) of the proposed method based on the open-source Texas Spoofing Test Battery (TEXBAT) dataset. The results showed that GCI-GANomaly improves the detection accuracy of traditional signal quality monitoring (SQM)-based methods by up to 30.8% and reduces the average FPR of existing RFF-based methods by 4.2% with much less training data while achieving slightly better average detection accuracy. We further evaluate the robustness (against spoofing power and time) of GCI-GANomaly based on a specific GPS signal dataset that we collected from the real-world constellation. The results showed that GCI-GANomaly achieves robust detection performance under varying spoofing power and shows acceptable stability as time elapses.

In the sixth generation and Internet of Things (6G-IoT) systems, impersonation attacks pose significant risks due to the high interconnectivity, and complexity of devices. This study develops a new, improved physical layer (PHY-layer) authentication method to counter impersonation attacks in an 6G-IoT system by leveraging radiation pattern feature in gain, phase, and position errors. We analyze the statistical behavior of radiation pattern with random errors in gain, phase, and position, and establish statistical models based on this analysis. Subsequently, we devise an authentication scheme that utilizes these statistical models to validate the legitimacy of the IoT device. Finally, a performance assessment has been carried out to validate the dependability and efficacy of the authentication scheme across diverse settings.

Authentication is a crucial method for ensuring the security of the unmanned aerial vehicle (UAV)-assisted communication systems; however, it also raises concerns about the leakage of private data. To address this problem, this paper focuses on the problem of identity authentication with privacy-preserving consideration. We propose a two-way privacy-preserving physical layer (PHY-Layer) authentication framework in a UAV-assisted multiple-input multiple-output (MIMO) communication system, by exploiting the carrier frequency offset (CFO) characterizing UAV identity and CFO-based session keys constructed by elliptic curve cryptography (ECC) to encrypt data frames. In particular, we first employ a MOOSE algorithm to extract the hardware fingerprint feature related to UAV, and based on the extracted CFO feature parameters, we devise an ECC-based algorithm for a session key negotiation. To achieve identity validation for the network parties, we establish a two-way authentication framework based on the resulting CFO feature parameters, and apply the CFO-based session key to encrypt data frames for avoiding the leakage of private data. Moreover, we derive the closed-form analytical expressions for the probabilities of the detection and false alarm for the rigorous performance analysis. Finally, we provide extensive numerical results to validate the proposed theoretical model and demonstrate its effectiveness in both identity authentication and privacy preservation. In comparison with the prior scheme, the proposed framework has a better robustness and privacy.

The fifth-generation mobile communication technology (5G) supports wireless data transmission across civil, commercial, industrial, and even military networks, where vast amounts of privacy data are constantly transmitted. However, the open nature of the air interface in 5G systems makes them vulnerable to various attacks. Physical-layer key generation (PKG) has been recognized as a highly promising technology for ensuring data security in 5G systems, while existing PKG schemes achieve low key entropy (i.e., low key randomness) due to poor channel probing and quantization. In this paper, we propose a PKG scheme with high key entropy, tailored to the unique characteristics of 5G systems. First, we design a channel probing method based on the demodulation reference signal in accordance with 5G standards, enhancing the similarity between channel measurements. Next, we introduce a quantization method based on local increment and monotonicity, which effectively leverages channel characteristics to achieve high-speed key generation and improve key entropy. Finally, we use both MATLAB simulation and real-world channel measurements to achieve comprehensive verification of the proposed scheme. The simulation results showed that the proposed scheme increases the key entropy by at least 25% with nearly the same key generation rate compared with existing PKG schemes for 5G systems. The experiment using real-world channel measurements also confirmed that the proposed scheme has higher key entropy.

This paper investigates secure communication in multi-UAV networks, where each UAV employs rate-splitting multiple access (RSMA) to simultaneously deliver downlink data services to multiple ground terminals (GTs) under eavesdropping threats. To enhance network security, we propose a two-stage collaborative RSMA transmission scheme. Based on this scheme, we study the optimization of multi-UAV cooperative trajectory, time-step sharing and jamming power (MUCTSJ) to maximize the network’s secrecy rate. Additionally, to ensure fairness in throughput allocation among GTs, we incorporate two typical UAV service principles—Channel Quality First (CQF) and Fair Service First (FSF)—into the optimization objectives. Given the non-convex and NP-hard nature of this optimization problem, we reformulate it as a Markov Decision Process (MDP) and introduce a multi-agent reinforcement learning (MARL) framework based on the Centralized Training and Decentralized Execution (CTDE) paradigm. To address the dynamic topological changes induced by UAV mobility and time-varying channel states, as well as the gradient interference among multiple learning tasks, we design a Multi-Task Attention Deep Recurrent Network (MTA-DRNN). This architecture effectively captures the distinct observed attributes of each UAV while enhancing the coordination between diverse actions, thereby improving the adaptability of the agent and the stability of training. Simulation results demonstrate the superiority of the proposed solution enhances the security of multi-UAV networks over other baseline schemes. Furthermore, deployment on corresponding hardware platforms confirms the solution’s effectiveness and robustness in practical applications.

This paper investigates the use of physical (PHY)-layer characteristics of wireless channels for identity authentication in Reconfigurable Intelligent Surface (RIS)-assisted wireless communication systems. We propose a generalized PHY-layer authentication scheme that involves both direct and cascaded channels for RIS-assisted IoT systems. The channels in each coherence block of the authentication phase are estimated using least squares estimation, and the estimation error covariance matrices are determined for performance evaluation. Leveraging the extracted features of the direct and cascaded channels, we establish authentication verification as a problem of differentiating two classes of changes. Auxiliary information in the form of second-order statistics assists the authentication verification procedure. Through statistical derivation using tools from statistical signal processing, matrix analysis, and composite hypothesis testing, we characterize false alarm and detection probabilities of the proposed scheme. Finally, we provide extensive numerical results to evaluate the performance and demonstrate the efficiency of the proposed authentication scheme across various system parameters.

Abstract This paper studies the problem of spatially correlated channel estimation for reconfigurable intelligent surface (RIS)‐assisted multiple‐input multiple‐output (MIMO) systems with arbitrarily correlated Gaussian perturbation. In particular, composite RIS channel estimation is first explored based on minimum mean square error (MMSE) method, and optimal training sequence design of pilots with MSE minimization. Applying the Kronecker‐structured model, correlated composite RIS‐related channels and correlated Gaussian perturbation are then characterized. The optimal training sequence structure and spatial training power allocation conditions are derived, and the choice of the optimal training sequence length is also analyzed. Finally, numerical results are provided to assess the performance of the proposed estimate method under different training sequence structures, the optimal length of the training sequence, and information statistics. Extensive numerical results show that the proposed estimate method has supreme performance compared to state of‐the‐art baseline methods (e.g. maximum likelihood and two‐sided linear channel estimation methods).

Satellite internet serves as an indispensable component of the upcoming sixth‐generation networks for providing global broadband internet access service. Due to the open nature of satellite‐ground communication, security issue in satellite internet has always been an important concern for both industry and academia. Although many researchers focus on secure communications in satellite internet, the literature is surprisingly sparse, with no comprehensive overview of the state‐of‐the‐art security techniques. This paper provides an in‐depth survey of secure communications for various satellite internet scenarios. Based on different security mechanisms, we first categorize the existing works of secure communications in satellite internet into two categories: cryptography‐based and physical layer security‐based. The former includes classical encryption‐based and quantum encryption‐based secure communication, and the latter is further divided into precoding‐based, cooperative jamming‐based, relay selection‐based, and physical‐layer authentication‐based secure communication depending on the applied techniques. Finally, we provide some future research directions.

While the millimeter-wave (mmWave) communication is less susceptible against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an attacker can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack.

This paper explores the joint secrecy and delay guarantees based on opportunistic jamming and link selection in a wireless relay system consisting of a source, a destination, multiple buffer-aided relays and a passive eavesdropper wiretapping over both hops. Based on the information of link state and buffer status, we design a novel transmission scheme based on link selection and jammer selection, which dynamically grants transmission links different priorities for packet delivery, such that the constraints on both secrecy outage probability and packet delay are jointly satisfied. To understand the performance of the new scheme, we then apply the bitmap technique and Markov chain theory to develop a complete theoretical framework for the modelling of three fundamental metrics, namely reliability outage probability, packet discarding probability and secrecy/delay constrained throughput (SDT). Finally, we provide extensive simulation and numerical results to validate our theoretical modelling, as well as to demonstrate that the proposed scheme is superior to the benchmarks in terms of SDT.

Communication performance relies largely on the availability of channel state information (CSI). This paper investigates the impact of outdated CSI on the achievable covert communication performance in a two-hop wireless relay system under two typical covert transmission schemes of rate-control transmission (RCT) and power-control transmission (PCT). We first apply the typical channel feedback delay model to determine the statistical distribution of outdated CSI, based on which we then develop theoretical models to depict the inherent relationship between outdated CSI and the fundamental covert performance metrics in terms of detection error probability (DEP) and covert rate (CR). With the help of these models, we further explore the optimization of DEP subject to the CR constraint as well as the optimization of CR subject to the DEP constraint to reveal the max-min DEP performance and the maximal CR performance with the outdated CSI. Finally, extensive numerical results are provided to illustrate the impact of outdated CSI on the covert communication performance.

This article investigates the secure communication in a two-hop cooperative wireless network, where a buffer-aided relay helps forward data from the source to destination, and a passive eavesdropper attempts to intercept data transmission from both the source and relay. To ensure the transmission security and communication quality of service (QoS) of the system, we design novel link selection policies for two cases that the instantaneous channel state information is available or unavailable at the source node. For evaluating the system performance, we then derive the closed-form expressions of end-to-end secrecy outage probability, system throughput and secrecy throughput, respectively. Based on the theoretical performance analysis, we further explore the performance optimization issues, revealing the insightful tradeoffs between the transmission security and QoS. An iterative algorithm is developed to identify the optimal setting of link selection parameters, which is helpful for the practical configuration of link selection policies to satisfy various system performance requirements. Finally, we conduct simulations to validate our theoretical performance analysis, and also provide extensive numerical results to illustrate the efficiency of the proposed link selection policies for ensuring the secure communication in a two-hop cooperative network.

A lot of works have been done to demonstrate that buffer-aided relaying can achieve a significant performance gain in cooperative wireless networks. However, the additional delay introduced by buffer has been largely neglected in available works, which is of significant importance for delay-sensitive networks. In this paper, we consider a two-hop buffer-aided relaying system suffering from eavesdropping, where every packet owns a limited lifetime. In order to satisfy a specific secrecy rate of the system, this paper proposes a novel security and lifetime (SELI)-aware relay selection scheme by balancing the security and lifetime constraints. Furthermore, to address the problem of the heterogeneous packets queuing in the buffer, the approach of Markov chain is embedded to model the packet occupancy process. With the help of this complete framework, we derive the exact expressions of performance metrics, including reliable outage probability, packet discarding probability and secrecy throughput. Finally, extensive simulation and numerical results are provided to validate our analysis and illustrate the proposed scheme can efficiently reduce the packet discarding ratio.